Data Analytics (with Professional Experience) MSc
MSc Data Analytics (with Professional Experience)
Do you want to get professional workplace experience of data analytics while qualifying with a Master's degree in the field?
On this MSc Data Analytics (with Professional Experience) degree course, you'll combine a 6-month work placement or a professional experience module with taught modules that develop your skills in data analysis, and the application and management of big data. You'll see how you can apply data analytics tools in emerging technologies and start-ups using the UK's only university-based SAP Next Gen Lab.
When you complete the course successfully, your Master's degree and professional experience could lead to career opportunities in areas such as data science and engineering, financial data analytics, social media analysis, political data analysis and cybersecurity.
MSc Data Analytics (with Professional Experience) entry requirements
Qualifications or experience
- A second-class honours degree in a relevant subject, or equivalent professional experience.
English language requirements
English language proficiency at a minimum of IELTS band 6.0 with no component score below 6.0.
If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
What you'll experience
On this Data Analytics (with Professional Experience) MSc degree you'll:
- Use the UK's only university-based SAP Next Gen Lab, featuring the world's leading cloud-based business software
- Work on your technological and technical abilities
- Build your previous studies and experience to postgraduate level
- Master the big data and data mining tools you need for your career such as Python, R and machine learning
- Analyse data from the University's original research in cosmology, health informatics and cybersecurity
- Develop your knowledge of applied data analytics and engineering, big data, business intelligence, and advanced data management
- Engage with important topics, such as the use of emerging technologies in data mining, business intelligence, machine learning and big data
- Plan and develop an in-depth research project, using your analytical skills to demonstrate understanding beyond taught material
Careers and opportunities
Data is a big source of economic value to businesses, government and individuals and the ability to analyse big data is expected to be one of the most sought-after skills over the next few decades. So this Master's in Data Analytics can significantly improve your career prospects.
In addition, this course focuses on your application and use of the latest data analytics and mining tools while on a professional experience placement. This adds to the tools and techniques you'll develop during workshops in our SAP Next Gen Lab and on our supercomputer.
When you finish the course, our Careers and Employability service can help you find a job that puts your skills to work. You can get help, advice and support from our Careers and Employability service for up to 5 years after you leave the University as you advance in your career.
What can you do with a Master's in Data Analytics?
Previous graduates have gone on to work in areas including:
- data science and engineering
- business intelligence
- financial data analytics
- cybersecurity data scientist/analyst
- health care informatics
- social media analysis
- political data analysis
You can also use your Data Analytics MSc to get entry to higher-level professional qualifications such as British Computer Society accreditation.
What jobs can you do with a Master's in Data Analytics?
Roles our graduates have taken on include:
- senior data scientist
- data engineer
- business intelligence analyst
- machine learning programmer
- PhD researcher
- machine learning programmer
- big data programmers and engineers
What's the future demand for data analytics graduates?
There's an increasing business demand for employees with data analysis, technical and soft skills. According to IBM, 90% of human data was made in the last 2 years and according to the Future of Jobs Report 2018, 85% of companies are likely or very likely to be using big data analytics.
New technologies in the data science field allow us to extract knowledge and value from this escalation in data and apply it to fields such as finance, cybersecurity, health care, social media analysis, politics and more. This means employers are increasingly looking for people who can deal with large data sets, understand business problems and bring people together to come up with solutions.
What you'll study on this MSc Data Analytics degree course
On this Master's degree in Data Analytics course, you'll study modules worth 190 credits.
The core modules are:
- Applied data and text analytics
- Big data applications
- Business intelligence
- Data management
- Master's engineering or study project
There are no optional modules on this course.
We use the best and most current research and professional practice alongside feedback from our students to make sure course content is relevant to your future career or further studies.
Therefore, some course content may change over time to reflect changes in the discipline or industry.
6-month professional experience module
In this module, you'll do a work placement or a professional experience programme. You'll do this for 6 months between September and March after you've completed your year of taught studies.
When on placement you'll have the opportunity to get involved in information systems research events and initiatives.
You can begin looking and applying for placements after completing your first teaching block. You'll get support from the Careers and Employability Centre and the Faculty of Technology Student Placement and Employability Centre in enhancing your employability skills, and in identifying and applying for suitable placements.
Note that work placements can't be guaranteed because it depends on their availability and the specific needs of placement providers. We'll give you the support you need to identify work placements but you'll be responsible for securing a placement successfully.
Professional experience programme
If you're unable to secure a work placement, you'll complete a professional experience programme designed to meet your career aspirations.
You'll further develop your employability and enterprise skills and prepare yourself for the workplace. This could be an entrepreneurship, industrial-related or consultancy project, or other activities appropriate for your career development.
This Data Analytics Master's degree adopts an innovative teaching style in the core units. There are no traditional lectures. Instead, lectures and practical classes are combined in long applied workshop sessions.
All teaching takes place in our computer labs, which are equipped with a variety of data analytics and data mining tools.
Teaching staff include experienced experts with relevant industry experience and research experience in data science, machine learning and big data subject areas. Teaching staff have worked in national and international companies as software engineers, data scientists and big data programmers.
You can access all teaching resources on Moodle, our virtual learning environment, from anywhere with a Web connection.
For more about the teaching activities for specific modules, see the module list above.
How you're assessed
You’ll be assessed through:
- written coursework
- practical assessments
You’ll be able to test your skills and knowledge informally before you do assessments that count towards your final mark. You can get feedback on all practice and formal assessments so you can improve in the future.
How you'll spend your time
We recommend you spend at least 40 hours a week studying for your Master's degree. You’ll be in timetabled teaching activities, such as applied workshop sessions, for about 20 hours a week. The rest of the time you’ll do independent study such as research, reading, coursework and project work, alone or in a group with others from your course. You'll need to be proactive in your learning, consolidating the material taught in the workshops.
Most timetabled teaching takes place during the day, Monday to Friday. There’s usually no teaching on Wednesday afternoons. Optional field trips may involve evening and weekend teaching or events. We encourage you to attend events and talks outside of the course curriculum to develop your understanding of current issues, to network and to explore options for future employment.
If you do a work placement, your working hours will depend on your employer and role but are likely to be around 35–40 hours a week.
The academic year for the taught elements of your course runs from September to early June with breaks at Christmas and Easter. It's divided into 2 teaching blocks and 2 assessment periods:
- September to December – teaching block 1
- January – assessment period 1
- January to May – teaching block 2 (includes Easter break)
- May to June – assessment period 2
Following the taught elements if your course, you'll work on your dissertation from early June until September and complete your 6-month professional experience module from September to March.
Extra learning support
You'll get face-to-face support from teaching and support staff when you need it. These include the following people and services:
Your personal tutor helps you make the transition to postgraduate study and gives you academic and personal support throughout your time at university.
As well as regular scheduled meetings with your personal tutor, they're also available at set times during the week if you want to chat with them about anything that can't wait until your next meeting.
Learning support tutors
You'll have help from a team of faculty learning support tutors. They can help you improve and develop your academic skills and support you in any area of your study in one-on-one and group sessions.
They can help you:
- master the mathematics skills you need to excel on your course
- understand engineering principles and how to apply them in any engineering discipline
- solve computing problems relevant to your course
- develop your knowledge of computer programming concepts and methods relevant to your course
- understand and use assignment feedback
All our labs and practical spaces are staffed by qualified laboratory support staff. They’ll support you in scheduled lab sessions and can give you one-to-one help when you do practical research projects.
Academic skills support
As well as support from faculty staff and your personal tutor, you can use the University’s Academic Skills Unit (ASK).
ASK provides one-to-one support in areas such as:
- Academic writing
- Note taking
- Time management
- Critical thinking
- Presentation skills
- Working in groups
- Revision, memory and exam techniques
If you have a disability or need extra support, the Additional Support and Disability Centre (ASDAC) will give you help, support and advice.
Library staff are available in person or by email, phone or online chat to help you make the most of the University’s library resources. You can also request one-to-one appointments and get support from a librarian who specialises in your subject area.
The library is open 24 hours a day, every day, in term time.
Tuition fees (2021 start)
UK/EU/Channel Islands and Isle of Man students
- Full-time: £7,950 (may be subject to annual increase)
(including Transition Scholarship)
- Full-time: £7,950 (may be subject to annual increase)
- Full-time: £17,600 (subject to annual increase)
You'll also need to pay a fee for your professional experience module, which you'll pay in the September following your taught studies.
Additional course costs
These course-related costs aren’t included in the tuition fees. So you’ll need to budget for them when you plan your spending.
Our accommodation section shows your accommodation options and highlights how much it costs to live in Portsmouth.
You’ll study up to 6 modules a year. You may have to read several recommended books or textbooks for each module.
You can borrow most of these from the Library. If you buy these, they may cost up to £60 each.
We recommend that you budget £75 a year for photocopying, memory sticks, DVDs and CDs, printing charges, binding and specialist printing.
If your final year includes a major project, there could be cost for transport or accommodation related to your research activities. The amount will depend on the project you choose.
There may be travel costs for optional internships/placements. These will vary depending on the nature of internship/placement and can range from £50 - £1000.
Start your application by following the link below:
Starting in 2021
- Full-time study September 2021 start (18 months)
If you're from outside of the UK, you can apply directly to us (above) or you can get an agent to help with your application. Check your country page for details of agents in your region. To find out what to include in your application, head to the how to apply page of our international students section.
If you don’t meet the English language requirements for this course yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
What skills and qualities do I need for this Data Analytics Master's degree course?
As well as meeting the entry requirements for the course, you'll ideally have a computer-related background and be looking to get skills in data analytics on an applied course.
You'll be an independent learner with an enquiring mind and the ability to communicate and work in groups. You'll also have a willingness to develop soft skills that are essential in information systems roles, such as an ability to see the bigger picture and work effectively in a group, communications skills, business awareness, curiosity and initiative.
Admissions terms and conditions
When you accept an offer to study at the University of Portsmouth, you also agree to abide by our Student Contract (which includes the University's relevant policies, rules and regulations). You should read and consider these before you apply.